Understands intent
The request is converted into a numerical representation for semantic comparison.
TAMGA INFRASTRUCTURE / CACHE
An intelligent cache layer that matches semantically similar requests with suitable previous responses instead of running the model again.
01 / TEMEL KAVRAM
An incoming query is evaluated by meaning, not only by exact text. When a sufficiently similar and valid result exists, the cached response is used instead of making another model call.
This approach can reduce latency and cost for repeated support questions, product information, documentation answers, and high-volume AI applications.
02 / FLOW
The request is converted into a numerical representation for semantic comparison.
Valid cache entries are searched to find the closest semantic match.
If the threshold is met, the stored response is returned; otherwise the selected AI model runs.
03 / BENEFIT
Cache hits reduce model token costs and response time. Similarity threshold, validity period, and scope can be shaped around application needs.
This page is an early product overview prototype; technical details will be expanded as development continues.Access models with one API key and scale your application.
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